With respect to a hypothesis search, a hypothesis having a pruning measure which exceeds a pruning threshold in the course of search is pruned, and a beam search for reducing the calculation amount is often performed for the purpose of efficiency of the search. As pruning measures of the beam search, two measures of the score difference from a maximum likelihood hypothesis and the number of hypotheses are generally widely used.
A score difference threshold is used to prune a hypothesis having a greater score difference from a maximum likelihood hypothesis than the threshold, and a hypothesis number threshold is used to prune a hypothesis having a larger hypothesis rank than the threshold.
These thresholds may be set to statically fixed values, and may be dynamically changed for each audio frame using certain criteria. For example, a technique is proposed in which acoustic reliability in each audio frame is calculated, and the score difference threshold is dynamically adjusted according thereto.
As shown in FIG. 7, a data processing device in the related art mentioned above includes a data input unit 101, a feature amount extraction unit 102, a hypothesis score calculation unit 103, a statistical model 104, a dynamic threshold setting unit 105, a hypothesis pruning unit 106, and a result output unit 107.
The data processing device in the related art having such a configuration operates as follows. That is, the data input unit 101 inputs data on which a search is performed, the feature amount extraction unit 102 extracts the feature amount from subject data, the hypothesis score calculation unit 103 calculates a score of the feature amount using the statistical model 104, the dynamic threshold setting unit 105 sets a threshold in each measure used for pruning, the hypothesis pruning unit 106 prunes hypotheses on the basis of the pruning threshold, and the result output unit 107 finally outputs a hypothesis having the highest score as a result (Non-Patent Document 1).